Implementation of AI-Driven Leaf Disease Detection & Multi-Vendor Agro System

Abstract

Agriculture is a critical sector in Bangladesh, and timely identification of crop diseases plays a vital role in ensuring productivity and reducing losses. This project, titled “Implementation of AI-Driven Leaf Disease Detection and Multi-Vendor Agro System (Krishi App)”, aims to develop a mobile-based solution that assists farmers in detecting leaf diseases and provides appropriate pesticide recommendations. The system integrates a deep learning model trained to identify various leaf diseases from images, delivering accurate results to the user through the Krishi App, developed with Flutter. The backend, built using Django REST Framework (DRF), handles data management, image processing, and communication between the app and the AI model. Additionally, the platform incorporates a multi-vendor system, enabling farmers to access and purchase recommended agro-products from verified suppliers efficiently. The proposed system not only helps in early detection and treatment of crop diseases but also streamlines the agro-product supply chain, supporting farmers in making informed decisions. The integration of AI, mobile technology, and e-commerce functionalities demonstrates a practical approach to modernizing agricultural practices, enhancing productivity, and contributing to the overall economic growth of the farming community.